Various processes are repeatable, and thus lend themselves to real time process monitoring. An example of such a repeatable process is ultrasonic welding, which involves the controlled application of high frequency vibration energy to interfacing surfaces of a clamped work piece. Surface friction generates heat that ultimately softens and bonds the interfacing surfaces. For a given work piece, the formation of multiple identical welds is often performed in a consistent, repeatable manner. Another example process is the cold testing of internal combustion engines in which the performance of the engine is tested without cylinder combustion, e.g., by driving the engine via an electric motor, including static and dynamic leak testing.
Conventional process control methods for repeatable processes involve monitoring fixed control variables against calibrated thresholds. That is, various closed-loop parameter-based control techniques may be applied to maintain certain parameters within a calibrated range. For example, welding power, displacement, and acoustic signals, as well as welding frequency, may be individually monitored and compared to corresponding thresholds in a welding process. The thresholds can be adjusted over time through trial and error, experimental, or deterministic methods. Such closed-loop threshold-based approaches can produce reasonably consistent process control parameters over time. However, work pieces of a substandard quality can still be manufactured using stable process control parameters, and thus closed-loop threshold-based control approaches do not always ensure stable work piece quality over time.